Cargando…
Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease
Chest CT is often used for localizing and quantitating pathologies associated with chronic obstructive pulmonary disease (COPD). While simple measurements of areas and volumes of emphysema and airway structure are common, these methods do not capture the structural complexity of the COPD lung. Since...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779609/ https://www.ncbi.nlm.nih.gov/pubmed/33408642 http://dx.doi.org/10.3389/fphys.2020.603197 |
_version_ | 1783631368785231872 |
---|---|
author | Tanabe, Naoya Sato, Susumu Suki, Béla Hirai, Toyohiro |
author_facet | Tanabe, Naoya Sato, Susumu Suki, Béla Hirai, Toyohiro |
author_sort | Tanabe, Naoya |
collection | PubMed |
description | Chest CT is often used for localizing and quantitating pathologies associated with chronic obstructive pulmonary disease (COPD). While simple measurements of areas and volumes of emphysema and airway structure are common, these methods do not capture the structural complexity of the COPD lung. Since the concept of fractals has been successfully applied to evaluate complexity of the lung, this review is aimed at describing the fractal properties of airway disease, emphysema, and vascular abnormalities in COPD. An object forms a fractal if it exhibits the property of self-similarity at different length scales of evaluations. This fractal property is governed by power-law functions characterized by the fractal dimension (FD). Power-laws can also manifest in other statistical descriptors of structure such as the size distribution of emphysema clusters characterized by the power-law exponent D. Although D is not the same as FD of emphysematous clusters, it is a useful index to characterize the spatial pattern of disease progression and predict clinical outcomes in patients with COPD. The FD of the airway tree shape and the D of the size distribution of airway branches have been proposed indexes of structural assessment and clinical predictions. Simulations are also useful to understand the mechanism of disease progression. Therefore, the power-law and fractal analysis of the parenchyma and airways, especially when combined with computer simulations, could lead to a better understanding of the structural alterations during the progression of COPD and help identify subjects at a high risk of severe COPD. |
format | Online Article Text |
id | pubmed-7779609 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77796092021-01-05 Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease Tanabe, Naoya Sato, Susumu Suki, Béla Hirai, Toyohiro Front Physiol Physiology Chest CT is often used for localizing and quantitating pathologies associated with chronic obstructive pulmonary disease (COPD). While simple measurements of areas and volumes of emphysema and airway structure are common, these methods do not capture the structural complexity of the COPD lung. Since the concept of fractals has been successfully applied to evaluate complexity of the lung, this review is aimed at describing the fractal properties of airway disease, emphysema, and vascular abnormalities in COPD. An object forms a fractal if it exhibits the property of self-similarity at different length scales of evaluations. This fractal property is governed by power-law functions characterized by the fractal dimension (FD). Power-laws can also manifest in other statistical descriptors of structure such as the size distribution of emphysema clusters characterized by the power-law exponent D. Although D is not the same as FD of emphysematous clusters, it is a useful index to characterize the spatial pattern of disease progression and predict clinical outcomes in patients with COPD. The FD of the airway tree shape and the D of the size distribution of airway branches have been proposed indexes of structural assessment and clinical predictions. Simulations are also useful to understand the mechanism of disease progression. Therefore, the power-law and fractal analysis of the parenchyma and airways, especially when combined with computer simulations, could lead to a better understanding of the structural alterations during the progression of COPD and help identify subjects at a high risk of severe COPD. Frontiers Media S.A. 2020-12-21 /pmc/articles/PMC7779609/ /pubmed/33408642 http://dx.doi.org/10.3389/fphys.2020.603197 Text en Copyright © 2020 Tanabe, Sato, Suki and Hirai. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Tanabe, Naoya Sato, Susumu Suki, Béla Hirai, Toyohiro Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease |
title | Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease |
title_full | Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease |
title_fullStr | Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease |
title_full_unstemmed | Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease |
title_short | Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease |
title_sort | fractal analysis of lung structure in chronic obstructive pulmonary disease |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779609/ https://www.ncbi.nlm.nih.gov/pubmed/33408642 http://dx.doi.org/10.3389/fphys.2020.603197 |
work_keys_str_mv | AT tanabenaoya fractalanalysisoflungstructureinchronicobstructivepulmonarydisease AT satosusumu fractalanalysisoflungstructureinchronicobstructivepulmonarydisease AT sukibela fractalanalysisoflungstructureinchronicobstructivepulmonarydisease AT hiraitoyohiro fractalanalysisoflungstructureinchronicobstructivepulmonarydisease |